Water Erosion Prediction Using the Revised Universal Soil Loss Equation (RUSLE) in a GIS Framework, Central Chile

Abstract

Soil erosion is a growing problem in Central Chile, particularly incoastal dry lands, where it can significantly decrease the productivityof rainfed agriculture and forestry. In this study, the RevisedUniversal Soil Loss Equation (RUSLE) was integrated into a GeographicInformation System (GIS), and used to evaluate the effects of differentcombinations of vegetative cover on soil erosion rates for Santo DomingoCounty in Central Chile. Implementing RUSLE in the GIS required acomplete description of the county's soils, climate, topography andcurrent land use/land cover. This information was compiled in rasters of25 x 25 m cells. RUSLE parameter values were assigned to each cell andannual soil loss estimates were generated on a cell by cell basis. Soillosses were estimated for the current and for three alternate scenariosof vegetative cover. Under current conditions, 39.7% of the county ispredicted to have low erosion rates ( 0.1 t ha(-1) yr(-1)), 39.8% hasintermediate rates (0.1-1.0 t ha(-1) yr(-1)), and 10.4% has higherosion rates (> 1.1 t ha(-1) yr(-1)). The remainder of the surface(10.2%) is not subject to erosion. Under the recommended alternatescenario, 89.3% of the county is predicted to have low erosion rates,and no areas are affected by high soil loss, reducing soil erosion to alevel that will not affect long term productivity. This paper describeshow RUSLE was implemented in the GIS, and the methodology and equationsused to evaluate the effects of the land use/land cover changes.